Search Results - (( using optimization method algorithm ) OR ( data relation tree algorithm ))
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Modeling forest fires risk using spatial decision tree
Published 2011“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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Conference or Workshop Item -
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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A matrix approach for minimum spanning tree in neutrosophic and application in medical waste management / Nur Haifa Ahmad Hayazim, Siti Nurain Zulkifli and Siti Nurhidayah Yaacob
Published 2022“…A numerical example related to finding the optimal route that can minimize the cost of solving the medical waste management is provided to show the effectiveness of the Prim's and Kruskal's algorithms with IVBN. …”
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Student Project -
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…To overcome this disadvantage, the Fireflies Algorithm (FA) was used because it has the ability to perform global searches and has quick convergence rate to optimize the initial clustering centers of the K-means algorithm, using a kind of weighted Euclidean distance to reduce the defects made by noise data and other uncertainties. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization
Published 2022“…One of the two input features is P (bar) and the other is T (k). ADA-DT (Adaboost Algorithm Decision Tree), ADA-LR (Adaboost Algorithm-Linear Regresion), and ADA-GRNN (Generative Regression Neural Network) models showed MAE of 6.54 ˣ 10ˉ⁵, 4.66 10 ˉ⁵, and 8.35 10 ˉ⁵, respectively. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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10
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…The Transformer model with transferred weights outperformed models trained from scratch using supervised learning. To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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An extreme gradient boosting for cancer feature extraction and classification
Published 2025“…This research focuses on improving gene selection for cancer classification using the XGBoost classifier, an efficient open-source implementation of the gradient-boosted trees algorithm. …”
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Gene Selection for Cancer Classification Based on XGBoost
Published 2025“…This research focuses on improving gene selection for cancer classification using the XGBoost classifier, an efficient open-source implementation of the gradient boosted trees algorithm. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…This algorithm provides a decision tree output to represent the knowledge model, enabled a faster classification of intra-urban classes, and disabled the subjectivities which are related to the interaction of the analyst. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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Cancer Prediction Based On Data Mining Using Decision Tree Algorithm
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Undergraduates Project Papers -
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Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
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Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob
Published 2014“…Besides that, Genetic Algorithm is applying to predict future sales based on the sales and product data. …”
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A study of graduate on time (GOT) for Ph.D students using decision tree model
Published 2019“…Therefore, this study aims to classify the Ph.D students into the group of “GOT achiever” and “non-GOT achiever” by using decision tree models. Historical data that related to all Ph.D students in a public university in Malaysia has been obtained directly from the database of Graduate Academic Information System (GAIS) in order to develop and compare the performance of decision tree models (Chi-square algorithm, Gini index algorithm, Entropy algorithm and an interactive decision tree). …”
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Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah
Published 2021“…Following the application of a new methodology on the real site, the result indicated the consistency of DTM values of all the algorithms at different flying heights but there were relatively small differences between all the algorithms used. …”
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